Menopause induces systemic inflammation that contributes to impaired endocrine and bone function, metabolic disease, obesity, as well as autoimmunity and cognitive decline. These observations highlight a critical need to understand the relationship between estrogen signaling and inflammation. The overarching problem in both our basic understanding and therapeutic targeting of nuclear receptors remains an almost complete lack of understanding of how small differences in ligands can drive widely different transcriptional outcomes, including pathway and tissue-selective signaling. The goal is to define the chemical, structural, and molecular rules for how the estrogen receptor-? (ER?) ligands control inflammatory gene expression through binding directly or indirectly to DNA and altering coregulator recruitment, which in turn controls gene expression. A systems biology approach to chemical biology and structural biology will be used to reveal rules for how ligands achieve signaling specificity. Specific Aim 1. Discover and characterize the epigenetic regulome that mediates differential effects of ER? ligands on the inflammatory response. Functional genomics approaches will be used to identify three sets of inflammatory gene sets that we hypothesize will show distinct rules for gene control: 1) TNF-induced, E2 modulated genes with composite ERE/?B sites 2) TNF-induced, E2 modulated genes with ER? tethering to ?B response elements; and 3) TNF-induce genes where ER? bounds but does not modulate. We will pick 3-4 representative genes from each category to target with an shRNA screen targeting all coregulators (~1200 shRNAmir targeting ~300 genes) to identify those required for ER? modulation. Coregulator-ER? interaction screens will be built and profiled with a compound library of 500 ER? ligands. Statistical models will enable identification of specific coregulator interactions that predict the inflammatory response to different classes of ligands and ties them to specific structural perturbations. Specific Aim 2. Identify the chemical and structural rules by which ER? transduces chemical structure into recruitment of specific signaling complexes that control inflammatory gene expression. Analysis of >100 crystal structures will be used to compute all atom distance matrices and use principal component analysis and multiple linear regression to identify ligand-induced perturbations that predict (1) regulation of specific genes, and (2) interaction with specific coregulators defined in Specific Aim 1. Impact: This work will identify structural rules for how ER? ligands differentially regulate inflammatory gene expression through the ligand-receptor interface allosterically controlling recruitment of an ensemble of specific coregulatory complexes. Identifying causal models for how ligands achieve signaling specificity impacts drug discovery and our understanding of the physiology underlying a variety of hormone-sensitive physiological systems and disease states, and should be readily translatable to other allosteric signaling systems including other nuclear receptors and GPCRs.